

'''simple docstring'''



from __future__ import annotations

SCREAMING_SNAKE_CASE_     = list[tuple[int, int]]

SCREAMING_SNAKE_CASE_     = [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

SCREAMING_SNAKE_CASE_     = ([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right

class       SCREAMING_SNAKE_CASE       :






      '''simple docstring'''






      def __init__(       self			:		Dict  ,       snake_case			:		int  ,       snake_case			:		int  ,       snake_case			:		int  ,       snake_case			:		int  ,       snake_case			:		float  ,       snake_case			:		Node | None  ,       ):



          """simple docstring"""





          _snake_case			:			int				       =		pos_x
          _snake_case			:			Optional[Any]				       =		pos_y
          _snake_case			:			Tuple				       =		(pos_y, pos_x)
          _snake_case			:			Any				       =		goal_x
          _snake_case			:			Dict				       =		goal_y
          _snake_case			:			Tuple				       =		g_cost
          _snake_case			:			Tuple				       =		parent
          _snake_case			:			Tuple				       =		self.calculate_heuristic()




      def 						__UpperCAmelCase      (       self			:		Optional[Any] ):



          """simple docstring"""





          _snake_case			:			Optional[int]				       =		abs(self.pos_x - self.goal_x )
          _snake_case			:			List[str]				       =		abs(self.pos_y - self.goal_y )
          return dx + dy




      def __lt__(       self			:		Dict  ,       snake_case			:		Tuple ):



          """simple docstring"""





          return self.f_cost < other.f_cost



class       SCREAMING_SNAKE_CASE       :






      '''simple docstring'''






      def __init__(       self			:		List[Any]  ,       snake_case			:		tuple[int, int]  ,       snake_case			:		tuple[int, int] ):



          """simple docstring"""





          _snake_case			:			Dict				       =		Node(start[1]  ,       start[0]  ,       goal[1]  ,       goal[0]  ,       0  ,       _A )
          _snake_case			:			Any				       =		Node(goal[1]  ,       goal[0]  ,       goal[1]  ,       goal[0]  ,       99999  ,       _A )

          _snake_case			:			List[str]				       =		[self.start]
          _snake_case			:			list[Node]				       =		[]

          _snake_case			:			Union[str, Any]				       =		False




      def 						__UpperCAmelCase      (       self			:		str ):



          """simple docstring"""





          while self.open_nodes:
              # Open Nodes are sorted using __lt__
              self.open_nodes.sort()
              _snake_case			:			Union[str, Any]				       =		self.open_nodes.pop(0 )

              if current_node.pos == self.target.pos:
                  _snake_case			:			Optional[int]				       =		True
                  return self.retrace_path(_A )

              self.closed_nodes.append(_A )
              _snake_case			:			List[str]				       =		self.get_successors(_A )

              for child_node in successors:
                  if child_node in self.closed_nodes:
                      continue

                  if child_node not in self.open_nodes:
                      self.open_nodes.append(_A )
                  else:
                      # retrieve the best current path
                      _snake_case			:			Union[str, Any]				       =		self.open_nodes.pop(self.open_nodes.index(_A ) )

                      if child_node.g_cost < better_node.g_cost:
                          self.open_nodes.append(_A )
                      else:
                          self.open_nodes.append(_A )

          if not self.reached:
              return [self.start.pos]
          return None




      def 						__UpperCAmelCase      (       self			:		Any  ,       snake_case			:		Node ):



          """simple docstring"""





          _snake_case			:			Tuple				       =		[]
          for action in delta:
              _snake_case			:			List[Any]				       =		parent.pos_x + action[1]
              _snake_case			:			List[str]				       =		parent.pos_y + action[0]

              if not (0 <= pos_x <= len(grid[0] ) - 1 and 0 <= pos_y <= len(_A ) - 1):
                  continue

              if grid[pos_y][pos_x] != 0:
                  continue

              successors.append(
                  Node(
                      _A  ,       _A  ,       self.target.pos_y  ,       self.target.pos_x  ,       parent.g_cost + 1  ,       _A  ,       ) )
          return successors




      def 						__UpperCAmelCase      (       self			:		Dict  ,       snake_case			:		Node | None ):



          """simple docstring"""





          _snake_case			:			List[str]				       =		node
          _snake_case			:			List[Any]				       =		[]
          while current_node is not None:
              path.append((current_node.pos_y, current_node.pos_x) )
              _snake_case			:			str				       =		current_node.parent
          path.reverse()
          return path


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE_     = (0, 0)
   SCREAMING_SNAKE_CASE_     = (len(grid) - 1, len(grid[0]) - 1)
   for elem in grid:
      print(elem)

   print("------")

   SCREAMING_SNAKE_CASE_     = GreedyBestFirst(init, goal)
   SCREAMING_SNAKE_CASE_     = greedy_bf.search()
   if path:
      for pos_x, pos_y in path:
         SCREAMING_SNAKE_CASE_     = 2

      for elem in grid:
         print(elem)











'''simple docstring'''





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
						import torch

						from transformers.generation import DisjunctiveConstraint


@require_torch
class  snake_case__      (					unittest.TestCase):




					def 		A      (  self  :		Union[str, Any]      )    ->							List[str]:
								# For consistency across different places the DisjunctiveConstraint is called,
								# dc.token_ids is a list of integers. It is also initialized only by integers.

								UpperCAmelCase_      :       Union[str, Any]          =       [[1, 2, 4], [1, 2, 3, 4]]
								UpperCAmelCase_      :       Dict          =       DisjunctiveConstraint(_A      )
								self.assertTrue(isinstance(dc.token_ids				, _A      )      )

								with self.assertRaises(_A      ):
											DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]      )      )

								with self.assertRaises(_A      ):
											DisjunctiveConstraint([torch.LongTensor([1, 2, 4]      ), torch.LongTensor([1, 2, 3, 4, 5]      )]      )




					def 		A      (  self  :		Optional[int]      )    ->							List[Any]:
								# We can't have constraints that are complete subsets of another. This leads to a preverse
								# interpretation of "constraint fulfillment": does generating [1,2,3] fulfill the constraint?
								# It would mean that it generated [1,2] which fulfills it, but it's in the middle of potentially
								# fulfilling [1,2,3,4]. If we believe that [1,2,3] does fulfill the constraint, then the algorithm
								# will necessarily never reach [1,2,3,4], giving users a false sense of control (better to just not allow it).
								UpperCAmelCase_      :       Optional[Any]          =       [[1, 2], [1, 2, 3, 4]]

								with self.assertRaises(_A      ):
											DisjunctiveConstraint(_A      )  # fails here




					def 		A      (  self  :		List[str]      )    ->							int:
								UpperCAmelCase_      :       Dict          =       [[1, 2, 3], [1, 2, 4]]

								UpperCAmelCase_      :       List[Any]          =       DisjunctiveConstraint(_A      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       List[str]          =       dc.update(1      )
								UpperCAmelCase_      :       int          =       stepped is True and completed is False and reset is False
								self.assertTrue(_A      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.current_seq == [1]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       Tuple          =       dc.update(2      )
								UpperCAmelCase_      :       Optional[int]          =       stepped is True and completed is False and reset is False
								self.assertTrue(_A      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.current_seq == [1, 2]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       Any          =       dc.update(3      )
								UpperCAmelCase_      :       List[Any]          =       stepped is True and completed is True and reset is False
								self.assertTrue(_A      )
								self.assertTrue(dc.completed      )  # Completed!
								self.assertTrue(dc.current_seq == [1, 2, 3]      )





					def 		A      (  self  :		List[Any]      )    ->							Any:
								UpperCAmelCase_      :       int          =       [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

								UpperCAmelCase_      :       str          =       DisjunctiveConstraint(_A      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       Tuple          =       dc.update(1      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.current_seq == [1]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       str          =       dc.update(2      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.current_seq == [1, 2]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       str          =       dc.update(4      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.current_seq == [1, 2, 4]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       Any          =       dc.update(5      )
								self.assertTrue(dc.completed      )  # Completed!
								self.assertTrue(dc.current_seq == [1, 2, 4, 5]      )

								dc.reset()

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       List[str]          =       dc.update(1      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.remaining() == 3      )
								self.assertTrue(dc.current_seq == [1]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       Optional[int]          =       dc.update(2      )
								self.assertTrue(not dc.completed      )
								self.assertTrue(dc.remaining() == 2      )
								self.assertTrue(dc.current_seq == [1, 2]      )

								UpperCAmelCase_    ,      UpperCAmelCase_    ,      UpperCAmelCase_      :       int          =       dc.update(5      )
								self.assertTrue(dc.completed      )  # Completed!
								self.assertTrue(dc.remaining() == 0      )
								self.assertTrue(dc.current_seq == [1, 2, 5]      )


